As computers are used more frequently to store, retrieve and analyze data, and as devices for storing data become increasingly larger and more efficient, it is now commonplace that new uses for computers are always being discovered. In the fields of graphics representation and image processing in particular, faster processors (coupled with memories having ever greater capacities) are engaged to solve problems of image analysis and storage.
Efficient processors and large memory devices are especially important in the field of image processing. An image comprises many regions, each of which is normally characterized in some manner and digitized so that a numerical value representative of each region can be derived, transformed, stored and retrieved at a later time for purposes of display or further processing. The smallest usable portion of an image is called a "pixel" (derived from "picture element"). An image is conventionally divided into one or more matrices of pixels, with each pixel having a unique location or address with respect to the boundaries of the image. The larger the image or the finer the pixels, the greater the capacity needed for a device to store data representative of the complete image. The need for processing units with improved efficiency proportional to an increased memory capacity is obvious.
One approach to processing an image is disclosed in "Intermediate-Level Vision--Building Vertex-String-Surface (V-S-S) Graphs" by C. Jacobus et al., Computer Graphics and Image Processing, Vol. 15, pp. 339-363 (1981), in which algorithms are presented for region aggregation, boundary string following and vertex detection and reconstruction. The image must be processed by means of a relatively complex computation which is, unfortunately, error-prone and time-consuming. Boundaries and their curvatures must be detected; to correct for discontinuities, the intermediate image and values must be edited either in post-processing or by utilizing graphic editing steps. The aforementioned system, as well as others relying on intense computation, represents the sort of cumbersome, often unacceptably inaccurate methods of digitizing and storing images that the present invention is meant to replace.
While the mere number of pixels in an image is a significant factor in predicting memory capacity, the quantity alone is not determinative. Along with the address of each pixel, there must be stored a qualitative value, such as the darkness, lightness or gray level of the pixel (if a black-and-white image is considered), or the color, tone or tint of the pixel (if a color image is considered). For these reasons, it should be understood that extraordinary amounts of data must be processed and stored, especially when large images or a plurality of images are handled.
In certain fields (such as real estate tax mapping, satellite photography and engineering schematics, for example), it is not unusual to handle thousands of images in a short period of time. In some cases, the amount of data representing a map to be recreated by computer processing is so great that even powerful "number-crunching" techniques are not adequate to accurately recreate the map. It is, therefore, desirable to redefine the map in a more simplified manner, i.e., by using a recoding technique to digitally define the map, using less information. Such a system that can deal adequately with complex image processing problems by using less digital data to define multiple maps, photographs and drawings would obviously be of great value.
In accordance with the present invention, there has been developed a method to recoat maps, using a "man-in-the-loop" technique. This new technique is a prescanning, "man-in-the-loop" method in which the various regions of a map are redefined, or recoated with simplified color coordinates designating boundary lines, and vertex coordinates defining map regions. In this manner, the amount of data necessary to recreate the map is greatly lessened. This not only reduces the amount of information that needs to be stored, but also eliminates or greatly reduces the amount of processing needed to recreate the map.
It would be advantageous to store data representative of an image in such a way so as to save processing time over and above the time spent utilizing conventional techniques.
It would also be advantageous to store data representative of an image in such a way so as to minimize the amount of data needed to recreate the stored image.
It would be a further advantage to provide a "man-in-the-loop" system capable of recoding a map with a minimum of digital information, whereby images can be digitized, stored and recreated without requiring undue memory or processing capacity.